Abstract
Risk and resilience are important and challenging issues in complex network systems since a single failure may trigger a whole collapse of the systems due to cascading effect. New theories, models, and methods are urgently demanded to deal with this challenge. In this paper, a coupled map lattices (CML) based approach is adopted to analyze the risk of cascading process in Watts-Strogatz (WS) small-world network and Barabási and Albert (BA) scale-free network, respectively. Then, to achieve an effective and robust system and provide guidance in countering the cascading failure, a modified CML model with recovery strategy factor is proposed. Numerical simulations are put forward based on small-world CML and scale-free CML. The simulation results reveal that appropriate recovery strategies would significantly improve the resilience of networks.
Highlights
In modern society, many real-world systems, such as Internet, transportation network, and power grid system [1,2,3], can be described by complex networks
Scale-free network based on coupled map lattices (CML), respectively
Cascading failure triggered by random external perturbation R, coupling coefficient ε, and recovery strategy RS is simulated and discussed, and the main findings and contributions of this paper are as follows: (1) For both small-world CML and scale-free CML, the cascading failure would be triggered after the initial failure when R ≥ 1, and the cascading process could be approximately divided into 3 phases; the failure rate is just about 10% when R = 2 and would not be over 40% for other R in small-world CML while it would be 100% when R ≥ 4 and 80% even R ≥ 2 in scale-free CML
Summary
Many real-world systems, such as Internet, transportation network, and power grid system [1,2,3], can be described by complex networks. The traumatic experiences bring an urgent need of the study of risk and safety of complex network system which has been a hot topic for scientific researchers in recent years [7,8,9,10]. Amongst these researches, cascading failure of complex networks has been one of the hottest topics. CML has been widely investigated to model the dynamical behaviors and cascading failure in complex systems [14,15,16,17,18].
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